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Description: RAVE is an audio processing/generativity based on deep learning. RAVE (Realtime Audio Variational autoEncoder) is a learning framework for generating a neural network model from audio data. RAVE allowing both fast and high-quality audio waveform synthesis (20x real-time at 48 kHz sampling rate on standard CPU). In Max and Pd, it is accompanied by its nn~ decoder, which enables these models to be used in real time for various applications, audio generativity/timbre transformation/transfer.
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Input types: Audio MIDI Text None Genre Metadata Image
Output types: Audio MIDI
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Technology: Not Specified Latent Consistency Model Latent Diffusion LSTM VAE Sequence-to-sequence neural network Transformer Suite of AI tools Diffusion Hierarchical Recurrent Neural Network (RNN) Autoregressive Convolutional Neural Network
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Has real time inference: Yes No Not known
Is free: Yes No Yes and No, depending on the plan Not known
Is open source: Yes No Not known
Are checkpoints available: Yes No Not known
Can finetune: Yes No Not known
Can train from scratch: Yes No Not known
Tags: text-to-audio MIDI text-prompt small-dataset open-source low-resource free checkpoints proprietary no-input image-to-audio
Guide: IRCAM provides very detailed guides to using the RAVE model with their tools as well as training the model on custom data. ### Using RAVE VST in your DAW [https://forum.ircam.fr/projects/detail/rave-vst/](https://forum.ircam.fr/projects/detail/rave-vst/) ### Neural Synthesis with RAVE in Max or Pure Data [https://forum.ircam.fr/article/detail/tutorial-neural-synthesis-in-max-8-with-rave/](https://forum.ircam.fr/article/detail/tutorial-neural-synthesis-in-max-8-with-rave/) ### Training RAVE models on custom data [https://forum.ircam.fr/article/detail/training-rave-models-on-custom-data/](https://forum.ircam.fr/article/detail/training-rave-models-on-custom-data/) ### GitHub repository [https://github.com/acids-ircam/RAVE](https://github.com/acids-ircam/RAVE) This field renders Markdown
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